Using curved angular intra-frame prediction to improve video coding efficiency

This article presents a new curved-based intra-frame prediction method for current and upcoming video coding standards. Our proposal extends conventional straight-line angular modes found on intra-prediction tools to model curved texture characteristics, enhancing the intra-frame prediction process. Our work targets the High Efficiency Video Coding (HEVC) standard for evaluation, although our curved-based method can be used by any other video coding standard. We model curved intra-frame prediction using an offset-based displacement calculation to each predicted sample. The proposal incurs a small bitstream overhead for transmitting the displacement information, which is offset by encoding efficiency gains. Experimental results demonstrate reduced residual energy; consequently, improving BD-Rate for the tested sequences. Evaluations applying eight curve displacement values show an average BD-Rate reduction of 2.69%, 2.49%, and 0.86% for All-Intra-8, All-Intra 10, and Random-Access configurations, respectively. The proposal allows further BD-Rate improvements, albeit at higher encoding complexity.     

Direction-adaptive fixed length discrete cosine transform framework for efficient H.264/AVC video coding

The 2D-discrete cosine transform (2D-DCT) is one of the popular transformation for video coding. Yet, 2D-DCT may not be able to efficiently represent video data with fewer coefficients for oblique featured blocks. To further improve the compression gain for such oblique featured video data, this paper presents a directional transform framework based on direction-adaptive fixed length discrete cosine transform (DAFL-DCT) for intra-, and inter-frame. The proposed framework selects the best suitable transform mode from eight proposed directional transform modes for each block, and modified zigzag scanning pattern rearranges these transformed coefficients into a 1D-array, suitable for entropy encoding. The proposed scheme is analysed on JM 18.6 of H.264/AVC platform. Performance comparisons have been made with respect to rate-distortion (RD), Bjontegaard metrics, encoding time etc. The proposed transform scheme outperforms the conventional 2D-DCT and other state-of-art techniques in terms of compression gain and subjective quality.     

Fast mode decision algorithm for intra prediction in H.264/AVC with integer transform and adaptive threshold

Compared with other existing video coding standards, H.264/AVC can achieve a significant improvement in compression performances. A robust criterion named the rate distortion optimization (RDO) is employed to select the optimal coding modes and motion vectors for each macroblock (MB), which achieves a high compression ratio while leading to a great increase in the complexity and computational load unfortunately. In this paper, a fast mode decision algorithm for H.264/AVC intra prediction based on integer transform and adaptive threshold is proposed. Before the intra prediction, integer transform operations on the original image are executed to find the directions of local textures. According to this direction, only a small part of the possible intra prediction modes are tested for RDO calculation at the first step. If the minimum mean absolute error (MMAE) of the reconstructed block corresponding to the best mode is smaller than an adaptive threshold which depends on the quantization parameter (QP), the RDO calculation is terminated. Otherwise, more possible modes need to be tested. The adaptive threshold aims to balance the compression performance and the computational load. Simulation results with various video sequences show that the fast mode decision algorithm proposed in this paper can accelerate the encoding speed significantly only with negligible PSNR loss or bit rate increment. This work is supported in part by China National Natural Science Foundation (CNSF) under Project No.60572045, the Ministry of Education of China Ph.D. Program Foundation under Project No.20050698033, and by a Cooperation Project (2005.7– 2007.7) with Microsoft Research Asia.     

基于FPGA的视频转换系统的实现

文章分析了视频转换中的关键技术：视频扫描转换和视频图象处理的基本原理，并给出了一种实际的实现方案，构建了以FPGA为控制核心的视频转换硬件系统。利用FPGA对整个系统进行编程配置，灵活地对系统进行控制，实现从非标准视频制式到标准视频制式以及标准制式之间的相互转换。     

一种基于瑞利分布的VBR视频流的小波模型

本文提出了一种新型的视频业务流模型,以Haar小波的多分辨率分析为基础,在尺度空间和小波空间分别建模,然后通过小波反变换得出仿真业务流.在最"粗"的尺度空间里,我们根据视频流的概率分布特点,采用基于瑞利(Rayleigh)分布的AR模型对尺度系数建模;在各个小波空间里,采用一般的高斯不相关小波模型(WIG,Wavelet Independent Guassian)建模.由于在尺度空间和小波空间针对各自的特点作了不同的处理,本文模型不但能较好拟合复杂业务流在各个时间尺度的概率分布特性,也能拟合其长时相关的特性.另外,在多尺度排队分析(MSQ,MultiScale Queue)的框架下,我们还推导出了基于本文模型的排队分析的理论结果.最后,通过对实际视频业务流数据仿真实验与排队分析验证了本文模型的有效性.     

No-reference pixel based video quality assessment for HEVC decoded video

This paper proposes a No-Reference (NR) Video Quality Assessment (VQA) method for videos subject to the distortion given by the High Efficiency Video Coding (HEVC) scheme. The assessment is performed without access to the bitstream. The proposed analysis is based on the transform coefficients estimated from the decoded video pixels, which is used to estimate the level of quantization. The information from this analysis is exploited to assess the video quality. HEVC transform coefficients are modeled with a joint-Cauchy probability density function in the proposed method. To generate VQA features the quantization step used in the Intra coding is estimated. We map the obtained HEVC features using an Elastic Net to predict subjective video quality scores, Mean Opinion Scores (MOS). The performance is verified on a dataset consisting of HEVC coded 4 K UHD (resolution equal to 3840 × 2160) video sequences at different bitrates and spanning a wide range of content. The results show that the quality scores computed by the proposed method are highly correlated with the mean subjective assessments.     

HEVC intra mode selection based on Rate Distortion (RD) cost and Sum of Absolute Difference (SAD)

High Efficiency Video Coding (HEVC) encoder provides higher compression efficiency by offering 35 intra modes. However, the encoding complexity is increased due to more modes are involved in the decision process. Therefore, it is desired to build a fast intra prediction algorithm that is practical for real time application. In this paper, a quadratic approach for reducing intra coding complexity is proposed. Firstly, the relationship between the RD-cost and the SAD is investigated. Secondly, a model is proposed to estimate the RD-cost of all 35 intra modes using the quadratic relation, thus avoiding the computation of entropy coding, Hadamard cost, distortion, and transform. Experimental results demonstrate that the average time saving of the proposed approach is 31–38%, while the BD-Bit Rate increment is only 0.62–1.37%, respectively.     

Content-adaptive parameters estimation for multi-dimensional rate control

Multi-dimensional rate control schemes have been recently utilized to adapt video streams to dynamic network conditions and heterogeneous devices. However, current multi-dimensional rate control methods, which estimate the model coefficients using fixed update duration, usually yield inaccurate parameters for dynamically changing video content. To address this problem, a content-adaptive parameters estimation scheme is proposed for multi-dimensional rate control. Firstly, we propose to estimate the parameters using dynamical update duration based on video content and the update duration of the model coefficients is determined by jointly considering the varying picture complexity and feedback information from the actual encoding results, which can improve the model parameter estimation accuracy. Secondly, a coarse-to-fine initial parameter calculation method is proposed to refine the initial frame rate according to the channel condition and the video sequence characteristics. Extensive experimental results show that the proposed solutions outperform the state-of-the-art schemes, especially for video sequences with high temporal and spatial complexity. Furthermore, our algorithm also slightly reduces the computational complexity as compared to related algorithms.     

An efficient six-parameter perspective motion model for VVC

Tilt and pan camera movements are common in computer games or social media videos. These types of videos contain numerous perspective transforms while today’s video codecs rely on translational and affine motion models for motion compensation. The general perspective motion model with 8 parameters (8PMM) has unreasonably high processing time. In this paper, the eight-parameter perspective transform is simplified into a six-parameter transform to keep the time complexity within an acceptable range while modeling the most relevant transforms. Also, two motion prediction modes, Advanced Perspective Motion Vector Prediction (APMVP) and Perspective Model Merge (PMM), are proposed. The implementation results show an average of 7.0% BD-rate reduction over H.266/VVC Test Model with a maximum of 20% encoding time overhead. The results also show a 71% processing time reduction in comparison to 8PMM while experiencing an average of 5.6% increase in BD-Rate. Much better visual quality is measured through VMAF quality meter.     

Highly Efficient Video Codec for Entertainment‐Quality

We present a novel video codec for supporting entertainment‐quality video. It has new coding tools such as an intra prediction with offset, integer sine transform, and enhanced block‐based adaptive loop filter. These tools are used adaptively in the processing of intra prediction, transform, and loop filtering. In our experiments, the proposed codec achieved an average reduction of 13.35% in BD‐rate relative to H.264/AVC for 720p sequences.     

Wavelet to DCT transcoding in transform domain

Wavelet to DCT transcoding provides inter-operability between standards using the two transforms for encoding. Transcoding in transform domain avoids inverse transform and re-transform operations and saves computation. In this paper, we propose new algorithms for transcoding wavelet coefficients to block DCT coefficients. In the first step, the wavelet coefficients are transformed into upsampled DCT coefficients. Subsequently, these trans-formed coefficients are synthesized in the block DCT space for transcoding. The proposed approach restricts all operations in the DCT domain that makes filtering involved in the synthesis process computationally efficient. The proposed technique could be used by the block DCT based services when the input is available as wavelet coefficients.     

Quantization of 3D-DCT Coefficients and Scan Order for Video Compression

This paper proposes a technique for generating the quantization values for 3D-DCT coefficients. The distribution of AC coefficients inside a transform cube is characterized by two regions, theshifted complement hyperboloidand theshifted hyperboloid,which capture the dominant and the less significant coefficients, respectively. An exponential function is used to determine the appropriate quantization values for the two regions. A quantization volume for the 3D-DCT is generated by using the function. The paper also describes a novel procedure for deriving the scan order for the quantized 3D-DCT coefficients. The proposed quantization volume has been tested on various standard test video sequences. The experiments show that the 3D-DCT video compression using the proposed quantization values produce high compression ratios with good visual quality for the reconstructed video frames. If desired, the parameter settings of the function can be further tuned for better visual quality. The proposed scan order was also found to be superior, in terms of compression ratio, to the 3D zig zag approach, which is an extension of the traditional 2D zig zag.     

基于三维子波变换和分级零树扫描的视频编码算法研究

本文研究了三维子波变换和分级三维零树混合视频编码算法,对图像序列体作３层２２子带时,空分解后,再对最低频子带进行４子带空间分解,对这个特殊分解的三维子波结构,推广了零树的概念,用ＨＶＳ量化模型对子波系统施加量化,用分级三维零树表示量化后的２５带子波系数,这一方案比单级零树方法节省约６％的码率,并且实现了空间和时间可尺主度化码流结构。     

ATM网中可变比特率小波视频编码和码率控制

本文提出了小波视频编码系统及其码率控制的新方法。对原始图像序列进行时间、水平和垂直三维小波分解,并采用改进的等级树集合分区的算法对小波系数进行量化。在图像组级上对该编码器进行码率控制,使其输出码流遵循漏桶控制器的参数,并对不同大小的漏桶缓冲器进行了讨论。仿真实验证明了该编码系统及其码率控制方法的有效性。     

Entropy Coding for a Hybrid Scheme with Motion Compensation in Subprimary Rate Video Transmission

Entropy coding has been investigated for motion-compensated interframe (MC) prediction followed by two-dimensional discrete cosine transform (DCT) for prediction error. In particular, variable word length coding methods for motion vector and transform coefficients have been discussed assuming low bit rate such as 384 kbits/s for transmission of videoconference sequences. For motion vector information, it is advantageous to employ a one-dimensional code set common to both horizontal and vertical components of motion vectors. The code set can be obtained using a combined distribution of the two components. In order to encode transform coefficients, different methods are applied to significant and insignificant blocks. Run-length coding is adequate for representing clusters of insignificant blocks. In encoding transform coefficients in significant blocks, a zone coding method which encodes transform coefficients within a minimum area enclosing all nonzero coefficients is suitable. Simulation of video sequences shows that a combination of the coding methods described here can achieve high coding efficiency for videoconference sequences.     

The quantized DCT and its application to DCT-based video coding

The two-dimensional (2-D) discrete cosine transform (DCT) and the subsequent quantization of the transform coefficients are two computationally demanding steps of any DCT-based video encoder. In this paper, we propose an efficient joint implementation of these two steps, where the precision in computing the DCT can be exchanged for a reduction in the computational complexity. First, the quantization is embedded in the DCT, thus eliminating the need to explicitly quantize the transform coefficients. A multiplierless integer implementation of the quantized DCT (QDCT) is then proposed that performs shift and add operations instead of full multiplications. A sequence of multiplierless QDCT algorithms is obtained with increasing precision and number of computations. Finally, further savings in computations are obtained by terminating the DCT computations whenever intermediate results indicate that the transform and quantization steps will likely result in a block of zero values. The proposed algorithms are applied to, and results are presented for, high-quality MPEG-2 and low bit rate H.263 video encoding.     

Parallel fast inter mode decision for H.264/AVC encoding

For H.264/AVC encoding, the mode selection process consumes a large proportion of the overall computation. To reduce this burden, various fast mode decision algorithms have been proposed. The current fast mode decision algorithms usually exploit the relationship among the coding modes and use the context-based approach to reduce the number of modes to be checked for both intra coding and inter coding. The parallel capacity of hardware architectures are also taken into consideration. However, almost all the parallel fast mode decision designs are focusing on intra coding. In this paper, a hardware friendly parallel fast inter mode decision method is proposed. With the proposed method, the inter mode decision can be conducted efficiently in one pass and significant encoding speedup can be achieved with negligible coding efficiency loss. Moreover, the proposed method can be easily mapped to hardware architecture which can be used for the real-time video encoding.     

SVM based approach for complexity control of HEVC intra coding

The High Efficiency Video Coding (HEVC) is adopted by various video applications in recent years. Because of its high computational demand, controlling the complexity of HEVC is of paramount importance to appeal to the varying requirements in many applications, including power-constrained video coding, video streaming, and cloud gaming. Most of the existing complexity control methods are only capable of considering a subset of the decision space, which leads to low coding efficiency. While the efficiency of machine learning methods such as Support Vector Machines (SVM) can be employed for higher precision decision making, the current SVM-based techniques for HEVC provide a fixed decision boundary which results in different coding complexities for different video content. Although this might be suitable for complexity reduction, it is not acceptable for complexity control. This paper proposes an adjustable classification approach for Coding Unit (CU) partitioning, which addresses the mentioned problems of complexity control. Firstly, a novel set of features for fast CU partitioning is designed using image processing techniques. Then, a flexible classification method based on SVM is proposed to model the CU partitioning problem. This approach allows adjusting the performance-complexity trade-off, even after the training phase. Using this model, and a novel adaptive thresholding technique, an algorithm is presented to deliver video encoding within the target coding complexity, while maximizing the coding efficiency. Experimental results justify the superiority of this method over the state-of-the-art methods, with target complexities ranging from 20% to 100%.